Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations251079
Missing cells27459
Missing cells (%)0.8%
Duplicate rows4046
Duplicate rows (%)1.6%
Total size in memory26.8 MiB
Average record size in memory112.0 B

Variable types

Categorical3
Text10
Numeric1

Alerts

Dataset has 4046 (1.6%) duplicate rowsDuplicates
fuel_consumption_l_100km has 26873 (10.7%) missing valuesMissing

Reproduction

Analysis started2025-10-09 03:47:36.329557
Analysis finished2025-10-09 03:47:46.505243
Duration10.18 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

brand
Categorical

Distinct47
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
volkswagen
33281 
mercedes-benz
27226 
audi
21161 
opel
20388 
bmw
19810 
Other values (42)
129213 

Length

Max length13
Median length11
Mean length6.439304
Min length3

Characters and Unicode

Total characters1616774
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowalfa-romeo
2nd rowalfa-romeo
3rd rowalfa-romeo
4th rowalfa-romeo
5th rowalfa-romeo

Common Values

ValueCountFrequency (%)
volkswagen33281
13.3%
mercedes-benz27226
10.8%
audi21161
 
8.4%
opel20388
 
8.1%
bmw19810
 
7.9%
ford18790
 
7.5%
skoda14039
 
5.6%
seat11949
 
4.8%
renault8694
 
3.5%
toyota8228
 
3.3%
Other values (37)67513
26.9%

Length

2025-10-09T11:47:46.587935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
volkswagen33281
13.3%
mercedes-benz27226
10.8%
audi21161
 
8.4%
opel20388
 
8.1%
bmw19810
 
7.9%
ford18790
 
7.5%
skoda14039
 
5.6%
seat11949
 
4.8%
renault8694
 
3.5%
toyota8228
 
3.3%
Other values (37)67513
26.9%

Most occurring characters

ValueCountFrequency (%)
e214526
 
13.3%
a150309
 
9.3%
o133918
 
8.3%
s103866
 
6.4%
d101592
 
6.3%
n98464
 
6.1%
r76839
 
4.8%
l72772
 
4.5%
i64956
 
4.0%
m60892
 
3.8%
Other values (15)538640
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)1616774
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e214526
 
13.3%
a150309
 
9.3%
o133918
 
8.3%
s103866
 
6.4%
d101592
 
6.3%
n98464
 
6.1%
r76839
 
4.8%
l72772
 
4.5%
i64956
 
4.0%
m60892
 
3.8%
Other values (15)538640
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1616774
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e214526
 
13.3%
a150309
 
9.3%
o133918
 
8.3%
s103866
 
6.4%
d101592
 
6.3%
n98464
 
6.1%
r76839
 
4.8%
l72772
 
4.5%
i64956
 
4.0%
m60892
 
3.8%
Other values (15)538640
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1616774
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e214526
 
13.3%
a150309
 
9.3%
o133918
 
8.3%
s103866
 
6.4%
d101592
 
6.3%
n98464
 
6.1%
r76839
 
4.8%
l72772
 
4.5%
i64956
 
4.0%
m60892
 
3.8%
Other values (15)538640
33.3%

model
Text

Distinct1312
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:46.876466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length33
Median length28
Mean length12.960865
Min length3

Characters and Unicode

Total characters3254201
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)< 0.1%

Sample

1st rowAlfa Romeo GTV
2nd rowAlfa Romeo 164
3rd rowAlfa Romeo Spider
4th rowAlfa Romeo Spider
5th rowAlfa Romeo 164
ValueCountFrequency (%)
volkswagen33281
 
5.9%
mercedes-benz27226
 
4.8%
audi21161
 
3.7%
opel20388
 
3.6%
bmw19810
 
3.5%
ford18790
 
3.3%
skoda14039
 
2.5%
seat11949
 
2.1%
golf10600
 
1.9%
renault8694
 
1.5%
Other values (984)378678
67.1%
2025-10-09T11:47:47.298313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313537
 
9.6%
e266619
 
8.2%
a243348
 
7.5%
o211184
 
6.5%
n146559
 
4.5%
r140155
 
4.3%
s126681
 
3.9%
d118457
 
3.6%
i115766
 
3.6%
l103441
 
3.2%
Other values (63)1468454
45.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)3254201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
313537
 
9.6%
e266619
 
8.2%
a243348
 
7.5%
o211184
 
6.5%
n146559
 
4.5%
r140155
 
4.3%
s126681
 
3.9%
d118457
 
3.6%
i115766
 
3.6%
l103441
 
3.2%
Other values (63)1468454
45.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3254201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
313537
 
9.6%
e266619
 
8.2%
a243348
 
7.5%
o211184
 
6.5%
n146559
 
4.5%
r140155
 
4.3%
s126681
 
3.9%
d118457
 
3.6%
i115766
 
3.6%
l103441
 
3.2%
Other values (63)1468454
45.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3254201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
313537
 
9.6%
e266619
 
8.2%
a243348
 
7.5%
o211184
 
6.5%
n146559
 
4.5%
r140155
 
4.3%
s126681
 
3.9%
d118457
 
3.6%
i115766
 
3.6%
l103441
 
3.2%
Other values (63)1468454
45.1%

color
Categorical

Distinct14
Distinct (%)< 0.1%
Missing166
Missing (%)0.1%
Memory size1.9 MiB
black
58720 
grey
46786 
white
40640 
silver
34362 
blue
32092 
Other values (9)
38313 

Length

Max length6
Median length5
Mean length4.6752978
Min length3

Characters and Unicode

Total characters1173093
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowred
2nd rowblack
3rd rowblack
4th rowblack
5th rowred

Common Values

ValueCountFrequency (%)
black58720
23.4%
grey46786
18.6%
white40640
16.2%
silver34362
13.7%
blue32092
12.8%
red21258
 
8.5%
brown4415
 
1.8%
green3500
 
1.4%
orange3367
 
1.3%
beige2420
 
1.0%
Other values (4)3353
 
1.3%

Length

2025-10-09T11:47:47.401773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
black58720
23.4%
grey46786
18.6%
white40640
16.2%
silver34362
13.7%
blue32092
12.8%
red21258
 
8.5%
brown4415
 
1.8%
green3500
 
1.4%
orange3367
 
1.3%
beige2420
 
1.0%
Other values (4)3353
 
1.3%

Most occurring characters

ValueCountFrequency (%)
e193118
16.5%
l129720
11.1%
r114274
9.7%
b98233
 
8.4%
i77830
 
6.6%
a62087
 
5.3%
c58720
 
5.0%
k58720
 
5.0%
g56653
 
4.8%
y48565
 
4.1%
Other values (10)275173
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)1173093
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e193118
16.5%
l129720
11.1%
r114274
9.7%
b98233
 
8.4%
i77830
 
6.6%
a62087
 
5.3%
c58720
 
5.0%
k58720
 
5.0%
g56653
 
4.8%
y48565
 
4.1%
Other values (10)275173
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1173093
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e193118
16.5%
l129720
11.1%
r114274
9.7%
b98233
 
8.4%
i77830
 
6.6%
a62087
 
5.3%
c58720
 
5.0%
k58720
 
5.0%
g56653
 
4.8%
y48565
 
4.1%
Other values (10)275173
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1173093
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e193118
16.5%
l129720
11.1%
r114274
9.7%
b98233
 
8.4%
i77830
 
6.6%
a62087
 
5.3%
c58720
 
5.0%
k58720
 
5.0%
g56653
 
4.8%
y48565
 
4.1%
Other values (10)275173
23.5%
Distinct433
Distinct (%)0.2%
Missing4
Missing (%)< 0.1%
Memory size1.9 MiB
2025-10-09T11:47:47.683401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.0001155
Min length2

Characters and Unicode

Total characters1757554
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)< 0.1%

Sample

1st row10/1995
2nd row02/1995
3rd row02/1995
4th row07/1995
5th row11/1996
ValueCountFrequency (%)
03/20234746
 
1.9%
05/20234128
 
1.6%
02/20233430
 
1.4%
04/20233250
 
1.3%
01/20232996
 
1.2%
05/20192920
 
1.2%
03/20192904
 
1.2%
04/20192729
 
1.1%
06/20232543
 
1.0%
06/20192532
 
1.0%
Other values (426)218943
87.2%
2025-10-09T11:47:48.070791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0517673
29.5%
2394771
22.5%
1264667
15.1%
/250882
14.3%
359119
 
3.4%
958182
 
3.3%
846460
 
2.6%
643628
 
2.5%
743127
 
2.5%
541426
 
2.4%
Other values (39)37619
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1757554
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0517673
29.5%
2394771
22.5%
1264667
15.1%
/250882
14.3%
359119
 
3.4%
958182
 
3.3%
846460
 
2.6%
643628
 
2.5%
743127
 
2.5%
541426
 
2.4%
Other values (39)37619
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1757554
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0517673
29.5%
2394771
22.5%
1264667
15.1%
/250882
14.3%
359119
 
3.4%
958182
 
3.3%
846460
 
2.6%
643628
 
2.5%
743127
 
2.5%
541426
 
2.4%
Other values (39)37619
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1757554
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0517673
29.5%
2394771
22.5%
1264667
15.1%
/250882
14.3%
359119
 
3.4%
958182
 
3.3%
846460
 
2.6%
643628
 
2.5%
743127
 
2.5%
541426
 
2.4%
Other values (39)37619
 
2.1%

year
Text

Distinct91
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:48.188577image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length4
Mean length4.0021308
Min length3

Characters and Unicode

Total characters1004851
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)< 0.1%

Sample

1st row1995
2nd row1995
3rd row1995
4th row1995
5th row1996
ValueCountFrequency (%)
201929225
11.6%
201824095
 
9.6%
202321097
 
8.4%
202220653
 
8.2%
201718940
 
7.5%
202018566
 
7.4%
202116022
 
6.4%
201615072
 
6.0%
201512712
 
5.1%
201410623
 
4.2%
Other values (82)64093
25.5%
2025-10-09T11:47:48.423456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2355576
35.4%
0305808
30.4%
1168039
16.7%
940320
 
4.0%
332554
 
3.2%
829422
 
2.9%
723313
 
2.3%
619284
 
1.9%
516299
 
1.6%
413286
 
1.3%
Other values (29)950
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1004851
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2355576
35.4%
0305808
30.4%
1168039
16.7%
940320
 
4.0%
332554
 
3.2%
829422
 
2.9%
723313
 
2.3%
619284
 
1.9%
516299
 
1.6%
413286
 
1.3%
Other values (29)950
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1004851
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2355576
35.4%
0305808
30.4%
1168039
16.7%
940320
 
4.0%
332554
 
3.2%
829422
 
2.9%
723313
 
2.3%
619284
 
1.9%
516299
 
1.6%
413286
 
1.3%
Other values (29)950
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1004851
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2355576
35.4%
0305808
30.4%
1168039
16.7%
940320
 
4.0%
332554
 
3.2%
829422
 
2.9%
723313
 
2.3%
619284
 
1.9%
516299
 
1.6%
413286
 
1.3%
Other values (29)950
 
0.1%
Distinct18228
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:48.698381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length32
Median length5
Mean length4.818129
Min length2

Characters and Unicode

Total characters1209731
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8539 ?
Unique (%)3.4%

Sample

1st row1300
2nd row24900
3rd row5900
4th row4900
5th row17950
ValueCountFrequency (%)
199901592
 
0.6%
169901404
 
0.6%
179901373
 
0.5%
159901316
 
0.5%
149901303
 
0.5%
189901281
 
0.5%
139901191
 
0.5%
249901157
 
0.5%
129901111
 
0.4%
229901074
 
0.4%
Other values (18238)238424
94.9%
2025-10-09T11:47:49.115418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0299465
24.8%
9261963
21.7%
1115823
 
9.6%
2101666
 
8.4%
591997
 
7.6%
886034
 
7.1%
483414
 
6.9%
369382
 
5.7%
752981
 
4.4%
645065
 
3.7%
Other values (60)1941
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)1209731
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0299465
24.8%
9261963
21.7%
1115823
 
9.6%
2101666
 
8.4%
591997
 
7.6%
886034
 
7.1%
483414
 
6.9%
369382
 
5.7%
752981
 
4.4%
645065
 
3.7%
Other values (60)1941
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1209731
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0299465
24.8%
9261963
21.7%
1115823
 
9.6%
2101666
 
8.4%
591997
 
7.6%
886034
 
7.1%
483414
 
6.9%
369382
 
5.7%
752981
 
4.4%
645065
 
3.7%
Other values (60)1941
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1209731
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0299465
24.8%
9261963
21.7%
1115823
 
9.6%
2101666
 
8.4%
591997
 
7.6%
886034
 
7.1%
483414
 
6.9%
369382
 
5.7%
752981
 
4.4%
645065
 
3.7%
Other values (60)1941
 
0.2%
Distinct596
Distinct (%)0.2%
Missing134
Missing (%)0.1%
Memory size1.9 MiB
2025-10-09T11:47:49.375483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length17
Median length3
Mean length2.6023272
Min length1

Characters and Unicode

Total characters653041
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)< 0.1%

Sample

1st row148
2nd row191
3rd row110
4th row110
5th row132
ValueCountFrequency (%)
11025986
 
10.3%
1409865
 
3.9%
969507
 
3.8%
819055
 
3.6%
858987
 
3.6%
1038297
 
3.3%
1006553
 
2.6%
746202
 
2.5%
1355999
 
2.4%
925783
 
2.3%
Other values (559)154940
61.7%
2025-10-09T11:47:49.771113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1177730
27.2%
0109346
16.7%
569903
 
10.7%
250427
 
7.7%
844977
 
6.9%
343831
 
6.7%
442685
 
6.5%
740850
 
6.3%
638139
 
5.8%
934158
 
5.2%
Other values (27)995
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)653041
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1177730
27.2%
0109346
16.7%
569903
 
10.7%
250427
 
7.7%
844977
 
6.9%
343831
 
6.7%
442685
 
6.5%
740850
 
6.3%
638139
 
5.8%
934158
 
5.2%
Other values (27)995
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)653041
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1177730
27.2%
0109346
16.7%
569903
 
10.7%
250427
 
7.7%
844977
 
6.9%
343831
 
6.7%
442685
 
6.5%
740850
 
6.3%
638139
 
5.8%
934158
 
5.2%
Other values (27)995
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)653041
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1177730
27.2%
0109346
16.7%
569903
 
10.7%
250427
 
7.7%
844977
 
6.9%
343831
 
6.7%
442685
 
6.5%
740850
 
6.3%
638139
 
5.8%
934158
 
5.2%
Other values (27)995
 
0.2%
Distinct578
Distinct (%)0.2%
Missing129
Missing (%)0.1%
Memory size1.9 MiB
2025-10-09T11:47:50.050695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length17
Median length3
Mean length2.8534728
Min length1

Characters and Unicode

Total characters716079
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique117 ?
Unique (%)< 0.1%

Sample

1st row201
2nd row260
3rd row150
4th row150
5th row179
ValueCountFrequency (%)
15025987
 
10.4%
1909866
 
3.9%
1319507
 
3.8%
1109068
 
3.6%
1168987
 
3.6%
1408298
 
3.3%
1366554
 
2.6%
1016202
 
2.5%
1845999
 
2.4%
1255785
 
2.3%
Other values (551)154820
61.7%
2025-10-09T11:47:50.457289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1208758
29.2%
0121450
17.0%
273507
 
10.3%
571949
 
10.0%
345526
 
6.4%
645060
 
6.3%
944281
 
6.2%
443522
 
6.1%
733309
 
4.7%
828194
 
3.9%
Other values (26)523
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)716079
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1208758
29.2%
0121450
17.0%
273507
 
10.3%
571949
 
10.0%
345526
 
6.4%
645060
 
6.3%
944281
 
6.2%
443522
 
6.1%
733309
 
4.7%
828194
 
3.9%
Other values (26)523
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)716079
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1208758
29.2%
0121450
17.0%
273507
 
10.3%
571949
 
10.0%
345526
 
6.4%
645060
 
6.3%
944281
 
6.2%
443522
 
6.1%
733309
 
4.7%
828194
 
3.9%
Other values (26)523
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)716079
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1208758
29.2%
0121450
17.0%
273507
 
10.3%
571949
 
10.0%
345526
 
6.4%
645060
 
6.3%
944281
 
6.2%
443522
 
6.1%
733309
 
4.7%
828194
 
3.9%
Other values (26)523
 
0.1%

transmission_type
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Automatic
131749 
Manual
117869 
Unknown
 
1144
Semi-automatic
 
317

Length

Max length14
Median length9
Mean length7.5888505
Min length6

Characters and Unicode

Total characters1905401
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowManual
2nd rowManual
3rd rowUnknown
4th rowManual
5th rowManual

Common Values

ValueCountFrequency (%)
Automatic131749
52.5%
Manual117869
46.9%
Unknown1144
 
0.5%
Semi-automatic317
 
0.1%

Length

2025-10-09T11:47:50.569556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-09T11:47:50.653769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
automatic131749
52.5%
manual117869
46.9%
unknown1144
 
0.5%
semi-automatic317
 
0.1%

Most occurring characters

ValueCountFrequency (%)
a368121
19.3%
t264132
13.9%
u249935
13.1%
o133210
 
7.0%
m132383
 
6.9%
i132383
 
6.9%
c132066
 
6.9%
A131749
 
6.9%
n121301
 
6.4%
l117869
 
6.2%
Other values (7)122252
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1905401
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a368121
19.3%
t264132
13.9%
u249935
13.1%
o133210
 
7.0%
m132383
 
6.9%
i132383
 
6.9%
c132066
 
6.9%
A131749
 
6.9%
n121301
 
6.4%
l117869
 
6.2%
Other values (7)122252
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1905401
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a368121
19.3%
t264132
13.9%
u249935
13.1%
o133210
 
7.0%
m132383
 
6.9%
i132383
 
6.9%
c132066
 
6.9%
A131749
 
6.9%
n121301
 
6.4%
l117869
 
6.2%
Other values (7)122252
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1905401
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a368121
19.3%
t264132
13.9%
u249935
13.1%
o133210
 
7.0%
m132383
 
6.9%
i132383
 
6.9%
c132066
 
6.9%
A131749
 
6.9%
n121301
 
6.4%
l117869
 
6.2%
Other values (7)122252
 
6.4%
Distinct136
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:50.748915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length6
Mean length6.0411544
Min length3

Characters and Unicode

Total characters1516807
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)< 0.1%

Sample

1st rowPetrol
2nd rowPetrol
3rd rowPetrol
4th rowPetrol
5th rowPetrol
ValueCountFrequency (%)
petrol143280
56.9%
diesel86897
34.5%
hybrid13083
 
5.2%
electric5967
 
2.4%
lpg1255
 
0.5%
cng508
 
0.2%
other178
 
0.1%
unknown96
 
< 0.1%
hydrogen82
 
< 0.1%
km34
 
< 0.1%
Other values (128)211
 
0.1%
2025-10-09T11:47:50.944316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e323301
21.3%
l236172
15.6%
r162590
10.7%
t149487
9.9%
P144536
9.5%
o143494
9.5%
i105973
 
7.0%
D86899
 
5.7%
s86897
 
5.7%
y13165
 
0.9%
Other values (39)64293
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)1516807
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e323301
21.3%
l236172
15.6%
r162590
10.7%
t149487
9.9%
P144536
9.5%
o143494
9.5%
i105973
 
7.0%
D86899
 
5.7%
s86897
 
5.7%
y13165
 
0.9%
Other values (39)64293
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1516807
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e323301
21.3%
l236172
15.6%
r162590
10.7%
t149487
9.9%
P144536
9.5%
o143494
9.5%
i105973
 
7.0%
D86899
 
5.7%
s86897
 
5.7%
y13165
 
0.9%
Other values (39)64293
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1516807
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e323301
21.3%
l236172
15.6%
r162590
10.7%
t149487
9.9%
P144536
9.5%
o143494
9.5%
i105973
 
7.0%
D86899
 
5.7%
s86897
 
5.7%
y13165
 
0.9%
Other values (39)64293
 
4.2%
Distinct621
Distinct (%)0.3%
Missing26873
Missing (%)10.7%
Memory size1.9 MiB
2025-10-09T11:47:51.219505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length17
Median length12
Mean length11.843791
Min length4

Characters and Unicode

Total characters2655449
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique238 ?
Unique (%)0.1%

Sample

1st row10,9 l/100 km
2nd row9,5 l/100 km
3rd row7,2 l/100 km
4th row9,5 l/100 km
5th row8,8 l/100 km
ValueCountFrequency (%)
km224008
33.3%
l/100222955
33.2%
4,98168
 
1.2%
5,17658
 
1.1%
5,57620
 
1.1%
5,97521
 
1.1%
5,37458
 
1.1%
56996
 
1.0%
5,76449
 
1.0%
5,46417
 
1.0%
Other values (499)167069
24.8%
2025-10-09T11:47:51.620782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0450193
17.0%
448113
16.9%
1260509
9.8%
k224668
8.5%
m224107
8.4%
/223634
8.4%
l222988
8.4%
,200655
7.6%
593226
 
3.5%
470962
 
2.7%
Other values (35)236394
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)2655449
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0450193
17.0%
448113
16.9%
1260509
9.8%
k224668
8.5%
m224107
8.4%
/223634
8.4%
l222988
8.4%
,200655
7.6%
593226
 
3.5%
470962
 
2.7%
Other values (35)236394
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2655449
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0450193
17.0%
448113
16.9%
1260509
9.8%
k224668
8.5%
m224107
8.4%
/223634
8.4%
l222988
8.4%
,200655
7.6%
593226
 
3.5%
470962
 
2.7%
Other values (35)236394
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2655449
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0450193
17.0%
448113
16.9%
1260509
9.8%
k224668
8.5%
m224107
8.4%
/223634
8.4%
l222988
8.4%
,200655
7.6%
593226
 
3.5%
470962
 
2.7%
Other values (35)236394
8.9%
Distinct1500
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:51.892972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.0186953
Min length3

Characters and Unicode

Total characters2013326
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique470 ?
Unique (%)0.2%

Sample

1st row260 g/km
2nd row- (g/km)
3rd row- (g/km)
4th row225 g/km
5th row- (g/km)
ValueCountFrequency (%)
g/km245650
48.6%
36707
 
7.3%
08533
 
1.7%
1194815
 
1.0%
km4336
 
0.9%
reichweite4324
 
0.9%
1143883
 
0.8%
1393389
 
0.7%
1303378
 
0.7%
1093363
 
0.7%
Other values (1199)187019
37.0%
2025-10-09T11:47:52.294050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
254318
12.6%
m249996
12.4%
k249987
12.4%
/246582
12.2%
g245650
12.2%
1215286
10.7%
270687
 
3.5%
351653
 
2.6%
050294
 
2.5%
448153
 
2.4%
Other values (38)330720
16.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)2013326
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
254318
12.6%
m249996
12.4%
k249987
12.4%
/246582
12.2%
g245650
12.2%
1215286
10.7%
270687
 
3.5%
351653
 
2.6%
050294
 
2.5%
448153
 
2.4%
Other values (38)330720
16.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2013326
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
254318
12.6%
m249996
12.4%
k249987
12.4%
/246582
12.2%
g245650
12.2%
1215286
10.7%
270687
 
3.5%
351653
 
2.6%
050294
 
2.5%
448153
 
2.4%
Other values (38)330720
16.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2013326
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
254318
12.6%
m249996
12.4%
k249987
12.4%
/246582
12.2%
g245650
12.2%
1215286
10.7%
270687
 
3.5%
351653
 
2.6%
050294
 
2.5%
448153
 
2.4%
Other values (38)330720
16.4%

mileage_in_km
Real number (ℝ)

Distinct71766
Distinct (%)28.6%
Missing152
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean85340.016
Minimum0
Maximum3800000
Zeros202
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2025-10-09T11:47:52.403767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile20
Q124904
median67500
Q3126500
95-th percentile232000
Maximum3800000
Range3800000
Interquartile range (IQR)101596

Descriptive statistics

Standard deviation78717.061
Coefficient of variation (CV)0.92239333
Kurtosis60.312251
Mean85340.016
Median Absolute Deviation (MAD)48342
Skewness3.0518562
Sum2.1414114 × 1010
Variance6.1963757 × 109
MonotonicityNot monotonic
2025-10-09T11:47:52.562381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106982
 
2.8%
501533
 
0.6%
151216
 
0.5%
201208
 
0.5%
51107
 
0.4%
1001062
 
0.4%
150000968
 
0.4%
100000959
 
0.4%
5000934
 
0.4%
125000774
 
0.3%
Other values (71756)234184
93.3%
ValueCountFrequency (%)
0202
 
0.1%
1296
 
0.1%
2255
 
0.1%
3108
 
< 0.1%
476
 
< 0.1%
51107
0.4%
6185
 
0.1%
7139
 
0.1%
8216
 
0.1%
9200
 
0.1%
ValueCountFrequency (%)
38000001
< 0.1%
28300001
< 0.1%
25800001
< 0.1%
23900001
< 0.1%
23000001
< 0.1%
22304561
< 0.1%
22234001
< 0.1%
21900001
< 0.1%
21065111
< 0.1%
21000001
< 0.1%
Distinct200945
Distinct (%)80.0%
Missing1
Missing (%)< 0.1%
Memory size1.9 MiB
2025-10-09T11:47:52.859160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length50
Median length39
Mean length34.755056
Min length1

Characters and Unicode

Total characters8726230
Distinct characters189
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182215 ?
Unique (%)72.6%

Sample

1st row2.0 V6 TB
2nd rowQ4 Allrad, 3.2L GTA
3rd rowALFA ROME 916
4th row2.0 16V Twin Spark L
5th row3.0i Super V6, absoluter Topzustand !
ValueCountFrequency (%)
navi33392
 
2.6%
25379
 
2.0%
2.023561
 
1.8%
led21239
 
1.7%
tdi20715
 
1.6%
tsi18786
 
1.5%
dsg14631
 
1.1%
pdc13871
 
1.1%
1.013330
 
1.0%
klima12567
 
1.0%
Other values (100424)1086186
84.6%
2025-10-09T11:47:53.279027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1042276
 
11.9%
i382671
 
4.4%
e376932
 
4.3%
a347252
 
4.0%
t300926
 
3.4%
A265750
 
3.0%
o265216
 
3.0%
r263116
 
3.0%
n247541
 
2.8%
S245460
 
2.8%
Other values (179)4989090
57.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)8726230
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1042276
 
11.9%
i382671
 
4.4%
e376932
 
4.3%
a347252
 
4.0%
t300926
 
3.4%
A265750
 
3.0%
o265216
 
3.0%
r263116
 
3.0%
n247541
 
2.8%
S245460
 
2.8%
Other values (179)4989090
57.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)8726230
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1042276
 
11.9%
i382671
 
4.4%
e376932
 
4.3%
a347252
 
4.0%
t300926
 
3.4%
A265750
 
3.0%
o265216
 
3.0%
r263116
 
3.0%
n247541
 
2.8%
S245460
 
2.8%
Other values (179)4989090
57.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)8726230
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1042276
 
11.9%
i382671
 
4.4%
e376932
 
4.3%
a347252
 
4.0%
t300926
 
3.4%
A265750
 
3.0%
o265216
 
3.0%
r263116
 
3.0%
n247541
 
2.8%
S245460
 
2.8%
Other values (179)4989090
57.2%

Interactions

2025-10-09T11:47:44.824073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-10-09T11:47:53.345496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
brandcolormileage_in_kmtransmission_type
brand1.0000.1120.0230.249
color0.1121.0000.0140.044
mileage_in_km0.0230.0141.0000.006
transmission_type0.2490.0440.0061.000

Missing values

2025-10-09T11:47:45.185818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-09T11:47:45.624988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-10-09T11:47:46.195014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

brandmodelcolorregistration_dateyearprice_in_europower_kwpower_pstransmission_typefuel_typefuel_consumption_l_100kmfuel_consumption_g_kmmileage_in_kmoffer_description
0alfa-romeoAlfa Romeo GTVred10/199519951300148201ManualPetrol10,9 l/100 km260 g/km160500.02.0 V6 TB
1alfa-romeoAlfa Romeo 164black02/1995199524900191260ManualPetrolNaN- (g/km)190000.0Q4 Allrad, 3.2L GTA
2alfa-romeoAlfa Romeo Spiderblack02/199519955900110150UnknownPetrolNaN- (g/km)129000.0ALFA ROME 916
3alfa-romeoAlfa Romeo Spiderblack07/199519954900110150ManualPetrol9,5 l/100 km225 g/km189500.02.0 16V Twin Spark L
4alfa-romeoAlfa Romeo 164red11/1996199617950132179ManualPetrol7,2 l/100 km- (g/km)96127.03.0i Super V6, absoluter Topzustand !
5alfa-romeoAlfa Romeo Spiderred04/199619967900110150ManualPetrol9,5 l/100 km225 g/km47307.02.0 16V Twin Spark
6alfa-romeoAlfa Romeo 145red12/199619963500110150ManualPetrol8,8 l/100 km210 g/km230000.0Quadrifoglio
7alfa-romeoAlfa Romeo 164black07/199619965500132179ManualPetrol13,4 l/100 km320 g/km168000.0(3.0) V6 Super
8alfa-romeoAlfa Romeo Spiderblack07/199619968990141192ManualPetrol11 l/100 km265 g/km168600.0|HU:neu|Klimaanlage|Youngtimer|
9alfa-romeoAlfa Romeo Spiderblack01/199619966976110150ManualPetrol9,2 l/100 km220 g/km99000.02.0 T.Spark L *Klima *2.Hand *Zahnriemen
brandmodelcolorregistration_dateyearprice_in_europower_kwpower_pstransmission_typefuel_typefuel_consumption_l_100kmfuel_consumption_g_kmmileage_in_kmoffer_description
251069volvoVolvo V90 Cross Countrysilver03/2023202377900173235AutomaticDiesel5,5 l/100 km144 g/km2500.0B5 D AWD Geartronic ULTIMATE
251070volvoVolvo V90 Cross Countrysilver01/2023202365422145197AutomaticDiesel6,5 l/100 km170 g/km1506.0B4 DIESEL PLUS AWD MY23 SELEKT
251071volvoVolvo XC60silver04/2023202381350228310AutomaticHybrid7,4 l/100 km167 g/km60.0XC 60 T8 AWD Ultimate Dark PHEV NAVI,AHK,STHZ,AHK,
251072volvoVolvo XC60silver05/2023202355400145197AutomaticDiesel5,6 l/100 km142 g/km5000.0B4 Autom. Plus Dark Keyless-Start/Klima/LED/BC
251073volvoVolvo XC60silver03/2023202354500145197AutomaticDiesel5,6 l/100 km142 g/km5900.0B4 Autom. Plus Dark Sitzhzg.
251074volvoVolvo XC40white04/2023202357990192261AutomaticHybridNaN43 km Reichweite1229.0Plus Bright T5 Recharge Intellisafe*Surround+Pilot
251075volvoVolvo XC90white03/2023202389690173235AutomaticDiesel7,6 l/100 km202 g/km4900.0B5 AWD Diesel Ultimate Dark 7-Sitzer Massage Four-
251076volvoVolvo V60white05/2023202361521145197AutomaticDiesel4,7 l/100 km125 g/km1531.0B4 D Plus Dark 145 kW, 5-türig (Diesel)
251077volvoVolvo XC40white05/2023202357890132179AutomaticHybridNaN45 km Reichweite1500.0T5 Recharge Plus Dark *Standh*360°*beh.Lenk
251078volvoVolvo XC40gold03/2023202352900160218AutomaticElectricNaN438 km Reichweite50.0Ultimate Recharge Twin Motor AHK GJR

Duplicate rows

Most frequently occurring

brandmodelcolorregistration_dateyearprice_in_europower_kwpower_pstransmission_typefuel_typefuel_consumption_l_100kmfuel_consumption_g_kmmileage_in_kmoffer_description# duplicates
1251fordFord Rangerwhite06/2023202344390151205AutomaticDiesel8,8 l/100 km230 g/km10.0Wildtrak 2.0 *NEUES MODELL*NAVI*CAM*LED*27
926fiatFiat 500Xwhite02/202320232998996131AutomaticPetrol5,9 l/100 km134 g/km10.0MY22 PIU Dolcevita Hybrid 1.5 AUTOMATIK26
892fiatFiat 500Cblue07/20222022211905271ManualHybrid4,8 l/100 km109 g/km99.01.0 GSE HYBRID DOLCEVITA PDC NAVI KLIMAAUTOMATIK22
891fiatFiat 500Cblue07/20222022209905271ManualHybrid4,8 l/100 km109 g/km99.01.0 GSE HYBRID DOLCEVITA PDC NAVI KLIMAAUTOMATIK19
792daciaDacia Sanderowhite04/20232023174456791ManualLPG4,9 l/100 km113 g/km10.0Stepway TCe100 ECO-G LPG/PARKP/8DISPLAY17
793daciaDacia Sanderowhite04/20232023176456791ManualLPG4,9 l/100 km113 g/km10.0Stepway TCe100 ECO-G LPG/PARKP/8DISPLAY16
3504toyotaToyota C-HRblue02/202320232999090122AutomaticHybrid3,8 l/100 km86 g/km10.01.8 Hybrid Team D *schnell Verfügbar*16
861fiatFiat 500red07/20222022191905271ManualHybrid4,6 l/100 km106 g/km99.01.0 GSE HYBRID RED BEATS PDC NAVI KLIMAAUTOMATIK14
1327fordFord Transit Customwhite06/202320233985096131ManualDiesel7,5 l/100 km198 g/km10.0Kombi 320 L1 9-SITZE PDC*TEMP*KLIMA14
2190opelOpel Astrasilver05/202320232559096131AutomaticPetrol5,6 l/100 km125 g/km500.0Business Edition 1.2*Navi*Shz*RFK*PDC*13